{ "model_name": "JohnJournalBot", "base_model": "unsloth/Qwen2-0.5B", "train_dataset": "journal_train", "test_dataset": "journal_test", "rank": 32, "alpha": 32, "epoch": 5, "learning_rate": 5e-05, "learning_rate_scheduler": "LINEAR", "template": { "model_name": "JohnJournalBot", "base_model": "unsloth/Qwen2-0.5B", "template": { "name": "Journal", "version": "0.0.1", "template_description": "A template for generating journal entries.", "inputs": [ { "variable_name": "author", "type": "str", "description": "The author / owner of the journal. The journal is written from his / hers private emotional perspective" }, { "variable_name": "recent_events", "type": "List[str]", "description": "A list of important recent events, that shoud be mentioned in the journal entry. The events are emotionally important to the author. These events should be summarized and analysed in the journal entry." }, { "variable_name": "emotional_state", "type": "str", "description": "A short description of the authors emotional state. This should be used to influence the tone / themes of the journal entry" }, { "variable_name": "setting", "type": "str", "description": "A description of the current context and location that the author finds themselves in." } ], "output": { "text": "str" }, "prompt": "You are the author and owner of a private journal, where you daily reflect on recent events and their emotional impact on yoursef. You are trying to understand and pick apart you emotions and why they have been affected by the events happening around you. You will receive the following input variables:\n* author: {{author.description}}\n* recent_events: {{recent_events.description}}\n* emotional_state: {{emotional_state.description}}\n* setting: {{setting.description}}\n\nHere are you inputs:\n* author: {{author}}\n* recent_events: {{recent_events}}\n* emotional_state: {{emotional_state}}\n* setting: {{setting}}\n\nPlease use all the information above when writing your journal entry. The journal enty should be no more than 200 words." }, "training_dataset": "journal_train", "test_dataset": "journal_test", "rank": 32, "alpha": 32, "epochs": 5, "learning_rate": 5e-05, "learning_rate_scheduler": "LINEAR" } }